In stochastic analysis, a part of the mathematical theory of probability, a predictable process is a stochastic process whose value is knowable at a prior time. The predictable processes form the smallest class that is closed under taking limits of sequences and contains all adapted left-continuous processes.
Mathematical definition
Discrete-time process
Given a filtered probability space
(
Ω
,
F
,
(
F
n
)
n
∈
N
,
P
)
{\displaystyle (\Omega ,{\mathcal {F}},({\mathcal {F}}_{n})_{n\in \mathbb {N} },\mathbb {P} )}
, then a stochastic process
(
X
n
)
n
∈
N
{\displaystyle (X_{n})_{n\in \mathbb {N} }}
is predictable if
X
n
+
1
{\displaystyle X_{n+1}}
is measurable with respect to the σ-algebra
F
n
{\displaystyle {\mathcal {F}}_{n}}
for each n.[1]
Continuous-time process
Given a filtered probability space
(
Ω
,
F
,
(
F
t
)
t
≥
0
,
P
)
{\displaystyle (\Omega ,{\mathcal {F}},({\mathcal {F}}_{t})_{t\geq 0},\mathbb {P} )}
, then a continuous-time stochastic process
(
X
t
)
t
≥
0
{\displaystyle (X_{t})_{t\geq 0}}
is predictable if
X
{\displaystyle X}
, considered as a mapping from
Ω
×
R
+
{\displaystyle \Omega \times \mathbb {R} _{+}}
, is measurable with respect to the σ-algebra generated by all left-continuous adapted processes.[2]
This σ-algebra is also called the predictable σ-algebra.
Examples
- Every deterministic process is a predictable process.
- Every continuous-time adapted process that is left continuous is a predictable process.
See also
References
- van Zanten, Harry (November 8, 2004). "An Introduction to Stochastic Processes in Continuous Time" (PDF). Archived from the original (pdf) on April 6, 2012. Retrieved October 14, 2011.
- "Predictable processes: properties" (PDF). Archived from the original (pdf) on March 31, 2012. Retrieved October 15, 2011.